{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Compute Key-Performance Indicators (KPIs) from the MLflow server.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# IMPORTS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import mlflow\n",
    "import pandas as pd\n",
    "import plotly.express as px"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# OPTIONS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.options.display.max_columns = None"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CONFIGS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "MAX_RESULTS = 100\n",
    "TRACKING_URI = \"http://localhost:5000\"\n",
    "REGISTRY_URI = \"http://localhost:5000\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CLIENTS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "client = mlflow.tracking.MlflowClient(tracking_uri=TRACKING_URI, registry_uri=REGISTRY_URI)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# INDICATORS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 7)\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>artifact_location</th>\n",
       "      <th>creation_time</th>\n",
       "      <th>experiment_id</th>\n",
       "      <th>last_update_time</th>\n",
       "      <th>lifecycle_stage</th>\n",
       "      <th>name</th>\n",
       "      <th>tags</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>file:///home/fmind/mlops-python-package/mlruns...</td>\n",
       "      <td>2024-12-14 14:35:02.439</td>\n",
       "      <td>300971336194126583</td>\n",
       "      <td>2024-12-14 14:35:02.439</td>\n",
       "      <td>active</td>\n",
       "      <td>bikes</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   artifact_location           creation_time  \\\n",
       "0  file:///home/fmind/mlops-python-package/mlruns... 2024-12-14 14:35:02.439   \n",
       "\n",
       "        experiment_id        last_update_time lifecycle_stage   name tags  \n",
       "0  300971336194126583 2024-12-14 14:35:02.439          active  bikes   {}  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "experiments = client.search_experiments(\n",
    "    view_type=mlflow.entities.ViewType.ALL, max_results=MAX_RESULTS, order_by=[\"creation_time DESC\"]\n",
    ")\n",
    "experiments = [dict(experiment) for experiment in experiments]\n",
    "experiments = pd.DataFrame(experiments).assign(\n",
    "    creation_time=lambda data: pd.to_datetime(data[\"creation_time\"], unit=\"ms\"),\n",
    "    last_update_time=lambda data: pd.to_datetime(data[\"last_update_time\"], unit=\"ms\"),\n",
    ")\n",
    "print(experiments.shape)\n",
    "experiments.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(27, 29)\n"
     ]
    },
    {
     "data": {
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>artifact_uri</th>\n",
       "      <th>end_time</th>\n",
       "      <th>experiment_id</th>\n",
       "      <th>lifecycle_stage</th>\n",
       "      <th>run_id</th>\n",
       "      <th>run_name</th>\n",
       "      <th>run_uuid</th>\n",
       "      <th>start_time</th>\n",
       "      <th>status</th>\n",
       "      <th>user_id</th>\n",
       "      <th>metrics</th>\n",
       "      <th>params</th>\n",
       "      <th>tags</th>\n",
       "      <th>run_time_secs</th>\n",
       "      <th>mlflow.user</th>\n",
       "      <th>mlflow.source.name</th>\n",
       "      <th>mlflow.source.type</th>\n",
       "      <th>mlflow.project.entryPoint</th>\n",
       "      <th>mlflow.source.git.commit</th>\n",
       "      <th>mlflow.source.git.repoURL</th>\n",
       "      <th>mlflow.gitRepoURL</th>\n",
       "      <th>mlflow.runName</th>\n",
       "      <th>mlflow.project.env</th>\n",
       "      <th>mlflow.project.backend</th>\n",
       "      <th>estimator_name</th>\n",
       "      <th>estimator_class</th>\n",
       "      <th>mlflow.log-model.history</th>\n",
       "      <th>mlflow.autologging</th>\n",
       "      <th>mlflow.parentRunId</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>file:///home/fmind/mlops-python-package/mlruns...</td>\n",
       "      <td>2024-12-14 14:42:28.056</td>\n",
       "      <td>300971336194126583</td>\n",
       "      <td>active</td>\n",
       "      <td>9923cb99c1824857b68c0bedb63f8446</td>\n",
       "      <td>Explanations</td>\n",
       "      <td>9923cb99c1824857b68c0bedb63f8446</td>\n",
       "      <td>2024-12-14 14:42:16.077</td>\n",
       "      <td>FINISHED</td>\n",
       "      <td>fmind</td>\n",
       "      <td>{}</td>\n",
       "      <td>{'conf_file': 'confs/explanations.yaml'}</td>\n",
       "      <td>{'mlflow.user': 'fmind', 'mlflow.source.name':...</td>\n",
       "      <td>11.979</td>\n",
       "      <td>fmind</td>\n",
       "      <td>file:///home/fmind/mlops-python-package</td>\n",
       "      <td>PROJECT</td>\n",
       "      <td>main</td>\n",
       "      <td>1a4b8a25a32f0e933a7db9ec47f763cc7bd17d1c</td>\n",
       "      <td>git@github.com:fmind/mlops-python-package</td>\n",
       "      <td>git@github.com:fmind/mlops-python-package</td>\n",
       "      <td>Explanations</td>\n",
       "      <td>virtualenv</td>\n",
       "      <td>local</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>file:///home/fmind/mlops-python-package/mlruns...</td>\n",
       "      <td>2024-12-14 14:42:13.733</td>\n",
       "      <td>300971336194126583</td>\n",
       "      <td>active</td>\n",
       "      <td>bfce074e34834054b84e5794450a4fa2</td>\n",
       "      <td>Evaluations</td>\n",
       "      <td>bfce074e34834054b84e5794450a4fa2</td>\n",
       "      <td>2024-12-14 14:42:07.488</td>\n",
       "      <td>FINISHED</td>\n",
       "      <td>fmind</td>\n",
       "      <td>{'example_count': 13903.0, 'mean_absolute_erro...</td>\n",
       "      <td>{'conf_file': 'confs/evaluations.yaml'}</td>\n",
       "      <td>{'mlflow.user': 'fmind', 'mlflow.source.name':...</td>\n",
       "      <td>6.245</td>\n",
       "      <td>fmind</td>\n",
       "      <td>file:///home/fmind/mlops-python-package</td>\n",
       "      <td>PROJECT</td>\n",
       "      <td>main</td>\n",
       "      <td>1a4b8a25a32f0e933a7db9ec47f763cc7bd17d1c</td>\n",
       "      <td>git@github.com:fmind/mlops-python-package</td>\n",
       "      <td>git@github.com:fmind/mlops-python-package</td>\n",
       "      <td>Evaluations</td>\n",
       "      <td>virtualenv</td>\n",
       "      <td>local</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>file:///home/fmind/mlops-python-package/mlruns...</td>\n",
       "      <td>2024-12-14 14:42:05.031</td>\n",
       "      <td>300971336194126583</td>\n",
       "      <td>active</td>\n",
       "      <td>5ebe28d67ed54300a177eb61825a6688</td>\n",
       "      <td>Inference</td>\n",
       "      <td>5ebe28d67ed54300a177eb61825a6688</td>\n",
       "      <td>2024-12-14 14:41:59.607</td>\n",
       "      <td>FINISHED</td>\n",
       "      <td>fmind</td>\n",
       "      <td>{}</td>\n",
       "      <td>{'conf_file': 'confs/inference.yaml'}</td>\n",
       "      <td>{'mlflow.user': 'fmind', 'mlflow.source.name':...</td>\n",
       "      <td>5.424</td>\n",
       "      <td>fmind</td>\n",
       "      <td>file:///home/fmind/mlops-python-package</td>\n",
       "      <td>PROJECT</td>\n",
       "      <td>main</td>\n",
       "      <td>1a4b8a25a32f0e933a7db9ec47f763cc7bd17d1c</td>\n",
       "      <td>git@github.com:fmind/mlops-python-package</td>\n",
       "      <td>git@github.com:fmind/mlops-python-package</td>\n",
       "      <td>Inference</td>\n",
       "      <td>virtualenv</td>\n",
       "      <td>local</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>file:///home/fmind/mlops-python-package/mlruns...</td>\n",
       "      <td>2024-12-14 14:41:57.245</td>\n",
       "      <td>300971336194126583</td>\n",
       "      <td>active</td>\n",
       "      <td>f29b930df5a54f1fa9ec5fe4b27df8b9</td>\n",
       "      <td>Promotion</td>\n",
       "      <td>f29b930df5a54f1fa9ec5fe4b27df8b9</td>\n",
       "      <td>2024-12-14 14:41:52.639</td>\n",
       "      <td>FINISHED</td>\n",
       "      <td>fmind</td>\n",
       "      <td>{}</td>\n",
       "      <td>{'conf_file': 'confs/promotion.yaml'}</td>\n",
       "      <td>{'mlflow.user': 'fmind', 'mlflow.source.name':...</td>\n",
       "      <td>4.606</td>\n",
       "      <td>fmind</td>\n",
       "      <td>file:///home/fmind/mlops-python-package</td>\n",
       "      <td>PROJECT</td>\n",
       "      <td>main</td>\n",
       "      <td>1a4b8a25a32f0e933a7db9ec47f763cc7bd17d1c</td>\n",
       "      <td>git@github.com:fmind/mlops-python-package</td>\n",
       "      <td>git@github.com:fmind/mlops-python-package</td>\n",
       "      <td>Promotion</td>\n",
       "      <td>virtualenv</td>\n",
       "      <td>local</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>file:///home/fmind/mlops-python-package/mlruns...</td>\n",
       "      <td>2024-12-14 14:41:49.910</td>\n",
       "      <td>300971336194126583</td>\n",
       "      <td>active</td>\n",
       "      <td>4753bf6b106845d19eca79b7cb329343</td>\n",
       "      <td>Training</td>\n",
       "      <td>4753bf6b106845d19eca79b7cb329343</td>\n",
       "      <td>2024-12-14 14:41:23.914</td>\n",
       "      <td>FINISHED</td>\n",
       "      <td>fmind</td>\n",
       "      <td>{'training_mean_squared_error': 1.280665585452...</td>\n",
       "      <td>{'conf_file': 'confs/training.yaml', 'memory':...</td>\n",
       "      <td>{'mlflow.user': 'fmind', 'mlflow.source.name':...</td>\n",
       "      <td>25.996</td>\n",
       "      <td>fmind</td>\n",
       "      <td>file:///home/fmind/mlops-python-package</td>\n",
       "      <td>PROJECT</td>\n",
       "      <td>main</td>\n",
       "      <td>1a4b8a25a32f0e933a7db9ec47f763cc7bd17d1c</td>\n",
       "      <td>git@github.com:fmind/mlops-python-package</td>\n",
       "      <td>git@github.com:fmind/mlops-python-package</td>\n",
       "      <td>Training</td>\n",
       "      <td>virtualenv</td>\n",
       "      <td>local</td>\n",
       "      <td>Pipeline</td>\n",
       "      <td>sklearn.pipeline.Pipeline</td>\n",
       "      <td>[{\"run_id\": \"4753bf6b106845d19eca79b7cb329343\"...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        artifact_uri                end_time  \\\n",
       "0  file:///home/fmind/mlops-python-package/mlruns... 2024-12-14 14:42:28.056   \n",
       "1  file:///home/fmind/mlops-python-package/mlruns... 2024-12-14 14:42:13.733   \n",
       "2  file:///home/fmind/mlops-python-package/mlruns... 2024-12-14 14:42:05.031   \n",
       "3  file:///home/fmind/mlops-python-package/mlruns... 2024-12-14 14:41:57.245   \n",
       "4  file:///home/fmind/mlops-python-package/mlruns... 2024-12-14 14:41:49.910   \n",
       "\n",
       "        experiment_id lifecycle_stage                            run_id  \\\n",
       "0  300971336194126583          active  9923cb99c1824857b68c0bedb63f8446   \n",
       "1  300971336194126583          active  bfce074e34834054b84e5794450a4fa2   \n",
       "2  300971336194126583          active  5ebe28d67ed54300a177eb61825a6688   \n",
       "3  300971336194126583          active  f29b930df5a54f1fa9ec5fe4b27df8b9   \n",
       "4  300971336194126583          active  4753bf6b106845d19eca79b7cb329343   \n",
       "\n",
       "       run_name                          run_uuid              start_time  \\\n",
       "0  Explanations  9923cb99c1824857b68c0bedb63f8446 2024-12-14 14:42:16.077   \n",
       "1   Evaluations  bfce074e34834054b84e5794450a4fa2 2024-12-14 14:42:07.488   \n",
       "2     Inference  5ebe28d67ed54300a177eb61825a6688 2024-12-14 14:41:59.607   \n",
       "3     Promotion  f29b930df5a54f1fa9ec5fe4b27df8b9 2024-12-14 14:41:52.639   \n",
       "4      Training  4753bf6b106845d19eca79b7cb329343 2024-12-14 14:41:23.914   \n",
       "\n",
       "     status user_id                                            metrics  \\\n",
       "0  FINISHED   fmind                                                 {}   \n",
       "1  FINISHED   fmind  {'example_count': 13903.0, 'mean_absolute_erro...   \n",
       "2  FINISHED   fmind                                                 {}   \n",
       "3  FINISHED   fmind                                                 {}   \n",
       "4  FINISHED   fmind  {'training_mean_squared_error': 1.280665585452...   \n",
       "\n",
       "                                              params  \\\n",
       "0           {'conf_file': 'confs/explanations.yaml'}   \n",
       "1            {'conf_file': 'confs/evaluations.yaml'}   \n",
       "2              {'conf_file': 'confs/inference.yaml'}   \n",
       "3              {'conf_file': 'confs/promotion.yaml'}   \n",
       "4  {'conf_file': 'confs/training.yaml', 'memory':...   \n",
       "\n",
       "                                                tags  run_time_secs  \\\n",
       "0  {'mlflow.user': 'fmind', 'mlflow.source.name':...         11.979   \n",
       "1  {'mlflow.user': 'fmind', 'mlflow.source.name':...          6.245   \n",
       "2  {'mlflow.user': 'fmind', 'mlflow.source.name':...          5.424   \n",
       "3  {'mlflow.user': 'fmind', 'mlflow.source.name':...          4.606   \n",
       "4  {'mlflow.user': 'fmind', 'mlflow.source.name':...         25.996   \n",
       "\n",
       "  mlflow.user                       mlflow.source.name mlflow.source.type  \\\n",
       "0       fmind  file:///home/fmind/mlops-python-package            PROJECT   \n",
       "1       fmind  file:///home/fmind/mlops-python-package            PROJECT   \n",
       "2       fmind  file:///home/fmind/mlops-python-package            PROJECT   \n",
       "3       fmind  file:///home/fmind/mlops-python-package            PROJECT   \n",
       "4       fmind  file:///home/fmind/mlops-python-package            PROJECT   \n",
       "\n",
       "  mlflow.project.entryPoint                  mlflow.source.git.commit  \\\n",
       "0                      main  1a4b8a25a32f0e933a7db9ec47f763cc7bd17d1c   \n",
       "1                      main  1a4b8a25a32f0e933a7db9ec47f763cc7bd17d1c   \n",
       "2                      main  1a4b8a25a32f0e933a7db9ec47f763cc7bd17d1c   \n",
       "3                      main  1a4b8a25a32f0e933a7db9ec47f763cc7bd17d1c   \n",
       "4                      main  1a4b8a25a32f0e933a7db9ec47f763cc7bd17d1c   \n",
       "\n",
       "                   mlflow.source.git.repoURL  \\\n",
       "0  git@github.com:fmind/mlops-python-package   \n",
       "1  git@github.com:fmind/mlops-python-package   \n",
       "2  git@github.com:fmind/mlops-python-package   \n",
       "3  git@github.com:fmind/mlops-python-package   \n",
       "4  git@github.com:fmind/mlops-python-package   \n",
       "\n",
       "                           mlflow.gitRepoURL mlflow.runName  \\\n",
       "0  git@github.com:fmind/mlops-python-package   Explanations   \n",
       "1  git@github.com:fmind/mlops-python-package    Evaluations   \n",
       "2  git@github.com:fmind/mlops-python-package      Inference   \n",
       "3  git@github.com:fmind/mlops-python-package      Promotion   \n",
       "4  git@github.com:fmind/mlops-python-package       Training   \n",
       "\n",
       "  mlflow.project.env mlflow.project.backend estimator_name  \\\n",
       "0         virtualenv                  local            NaN   \n",
       "1         virtualenv                  local            NaN   \n",
       "2         virtualenv                  local            NaN   \n",
       "3         virtualenv                  local            NaN   \n",
       "4         virtualenv                  local       Pipeline   \n",
       "\n",
       "             estimator_class  \\\n",
       "0                        NaN   \n",
       "1                        NaN   \n",
       "2                        NaN   \n",
       "3                        NaN   \n",
       "4  sklearn.pipeline.Pipeline   \n",
       "\n",
       "                            mlflow.log-model.history mlflow.autologging  \\\n",
       "0                                                NaN                NaN   \n",
       "1                                                NaN                NaN   \n",
       "2                                                NaN                NaN   \n",
       "3                                                NaN                NaN   \n",
       "4  [{\"run_id\": \"4753bf6b106845d19eca79b7cb329343\"...                NaN   \n",
       "\n",
       "  mlflow.parentRunId  \n",
       "0                NaN  \n",
       "1                NaN  \n",
       "2                NaN  \n",
       "3                NaN  \n",
       "4                NaN  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "runs = client.search_runs(\n",
    "    experiment_ids=experiments[\"experiment_id\"].unique(),\n",
    "    run_view_type=mlflow.entities.ViewType.ALL,\n",
    "    max_results=MAX_RESULTS,\n",
    "    order_by=[\"created DESC\"],\n",
    ")\n",
    "runs = [dict(run.info) | dict(run.data) for run in runs]\n",
    "runs = pd.DataFrame(runs).assign(\n",
    "    end_time=lambda data: pd.to_datetime(data[\"end_time\"], unit=\"ms\"),\n",
    "    start_time=lambda data: pd.to_datetime(data[\"start_time\"], unit=\"ms\"),\n",
    "    run_time_secs=lambda data: (data[\"end_time\"] - data[\"start_time\"]).map(\n",
    "        lambda t: t.total_seconds()\n",
    "    ),\n",
    ")\n",
    "runs = pd.concat([runs, pd.json_normalize(runs[\"tags\"])], axis=\"columns\")\n",
    "print(runs.shape)\n",
    "runs.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 6)\n"
     ]
    },
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>aliases</th>\n",
       "      <th>creation_timestamp</th>\n",
       "      <th>description</th>\n",
       "      <th>last_updated_timestamp</th>\n",
       "      <th>name</th>\n",
       "      <th>tags</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>{'Champion': '3'}</td>\n",
       "      <td>2024-12-14 14:37:45.482</td>\n",
       "      <td></td>\n",
       "      <td>2024-12-14 14:41:56.590</td>\n",
       "      <td>bikes</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             aliases      creation_timestamp description  \\\n",
       "0  {'Champion': '3'} 2024-12-14 14:37:45.482               \n",
       "\n",
       "   last_updated_timestamp   name tags  \n",
       "0 2024-12-14 14:41:56.590  bikes   {}  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "models = client.search_registered_models(\n",
    "    max_results=MAX_RESULTS, order_by=[\"creation_timestamp DESC\"]\n",
    ")\n",
    "models = [dict(model) for model in models]\n",
    "models = (\n",
    "    pd.DataFrame(models)\n",
    "    .assign(\n",
    "        creation_timestamp=lambda data: pd.to_datetime(data[\"creation_timestamp\"], unit=\"ms\"),\n",
    "        last_updated_timestamp=lambda data: pd.to_datetime(\n",
    "            data[\"last_updated_timestamp\"], unit=\"ms\"\n",
    "        ),\n",
    "    )\n",
    "    .drop(columns=[\"latest_versions\"])\n",
    ")\n",
    "print(models.shape)\n",
    "models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(3, 14)\n"
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       "      <th>aliases</th>\n",
       "      <th>creation_timestamp</th>\n",
       "      <th>current_stage</th>\n",
       "      <th>description</th>\n",
       "      <th>last_updated_timestamp</th>\n",
       "      <th>name</th>\n",
       "      <th>run_id</th>\n",
       "      <th>run_link</th>\n",
       "      <th>source</th>\n",
       "      <th>status</th>\n",
       "      <th>status_message</th>\n",
       "      <th>tags</th>\n",
       "      <th>user_id</th>\n",
       "      <th>version</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Champion</td>\n",
       "      <td>2024-12-14 14:41:48.936</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>2024-12-14 14:41:48.936</td>\n",
       "      <td>bikes</td>\n",
       "      <td>4753bf6b106845d19eca79b7cb329343</td>\n",
       "      <td></td>\n",
       "      <td>file:///home/fmind/mlops-python-package/mlruns...</td>\n",
       "      <td>READY</td>\n",
       "      <td></td>\n",
       "      <td>{}</td>\n",
       "      <td></td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>None</td>\n",
       "      <td>2024-12-14 14:39:49.417</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>2024-12-14 14:39:49.417</td>\n",
       "      <td>bikes</td>\n",
       "      <td>ae9f673f6b264240bb79ffd94ca49fe2</td>\n",
       "      <td></td>\n",
       "      <td>file:///home/fmind/mlops-python-package/mlruns...</td>\n",
       "      <td>READY</td>\n",
       "      <td></td>\n",
       "      <td>{}</td>\n",
       "      <td></td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>None</td>\n",
       "      <td>2024-12-14 14:37:45.487</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>2024-12-14 14:37:45.487</td>\n",
       "      <td>bikes</td>\n",
       "      <td>d2aed973c12b475f849743599f7bc973</td>\n",
       "      <td></td>\n",
       "      <td>file:///home/fmind/mlops-python-package/mlruns...</td>\n",
       "      <td>READY</td>\n",
       "      <td></td>\n",
       "      <td>{}</td>\n",
       "      <td></td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    aliases      creation_timestamp current_stage description  \\\n",
       "0  Champion 2024-12-14 14:41:48.936          None               \n",
       "1      None 2024-12-14 14:39:49.417          None               \n",
       "2      None 2024-12-14 14:37:45.487          None               \n",
       "\n",
       "   last_updated_timestamp   name                            run_id run_link  \\\n",
       "0 2024-12-14 14:41:48.936  bikes  4753bf6b106845d19eca79b7cb329343            \n",
       "1 2024-12-14 14:39:49.417  bikes  ae9f673f6b264240bb79ffd94ca49fe2            \n",
       "2 2024-12-14 14:37:45.487  bikes  d2aed973c12b475f849743599f7bc973            \n",
       "\n",
       "                                              source status status_message  \\\n",
       "0  file:///home/fmind/mlops-python-package/mlruns...  READY                  \n",
       "1  file:///home/fmind/mlops-python-package/mlruns...  READY                  \n",
       "2  file:///home/fmind/mlops-python-package/mlruns...  READY                  \n",
       "\n",
       "  tags user_id version  \n",
       "0   {}               3  \n",
       "1   {}               2  \n",
       "2   {}               1  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "versions = client.search_model_versions(\n",
    "    max_results=MAX_RESULTS, order_by=[\"creation_timestamp DESC\"]\n",
    ")\n",
    "versions = [dict(version) for version in versions]\n",
    "versions = pd.DataFrame(versions).assign(\n",
    "    aliases=lambda data: data[\"aliases\"].map(lambda x: x[0] if len(x) else None),\n",
    "    creation_timestamp=lambda data: pd.to_datetime(data[\"creation_timestamp\"], unit=\"ms\"),\n",
    "    last_updated_timestamp=lambda data: pd.to_datetime(data[\"last_updated_timestamp\"], unit=\"ms\"),\n",
    ")\n",
    "print(versions.shape)\n",
    "versions.head()"
   ]
  },
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   "metadata": {},
   "source": [
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   "metadata": {},
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     },
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   ],
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